CN104332984B - A kind of node voltage based on noise like influences each other the on-line identification method of the factor - Google Patents
A kind of node voltage based on noise like influences each other the on-line identification method of the factor Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J1/00—Circuit arrangements for dc mains or dc distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J1/00—Circuit arrangements for dc mains or dc distribution networks
- H02J1/08—Three-wire systems; Systems having more than three wires
- H02J1/082—Plural DC voltage, e.g. DC supply voltage with at least two different DC voltage levels
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/60—Arrangements for transfer of electric power between AC networks or generators via a high voltage DC link [HVCD]
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Abstract
The present invention relates to the node voltage of a kind of electrically-based system voltage noise-like signal influence each other factor discrimination method, belong to Power System Stability Analysis evaluation areas.The application conditions of the factor and applicable object first, it is settled that voltage influences each other: voltage influences each other the effect of influencing each other that the factor is mainly used in weighing in many straight-flow systems between each straight-flow system, based on systematic steady state or steady-state process temporarily；System is carried out linear simplifiation, sets up and send straight-flow system Node Voltage Sensitivity identification model more；Gather each node voltage signal in power system, carry out signal filtering, amplitude limit, go trend etc. to process, obtain node voltage noise-like signal；The method identification using multiple linear successive Regression obtains the factor that influences each other between DC line change of current busbar voltage.The inventive method may be used for the interaction strength between monitoring system, provides criterion for system local stability degree, is effectively improved power system stability risk profile efficiency, reduces the cost of site test.
Description
Technical field
The present invention relates to a kind of node voltage based on noise like influence each other the on-line identification method of the factor, belong to power system
Stability analysis evaluation areas.
Background technology
Along with the continuous construction of China's high voltage DC engineering, occur in that alternating current-direct current interconnected power grid many, for many direct currents
For system, its drop point is tight, electrical distance near, has strong coupling feature between each straight-flow system.With pure AC system or
Single straight-flow system is compared, and the degree of stability of many straight-flow systems is not only relevant with this straight-flow system electric network composition, control mode etc.,
Also being affected by with other straight-flow system adjacent, the interaction property between the most straight-flow systems is to whole ac and dc systems
Safety and stability has a great impact, and the interaction between the many straight-flow systems of reasonable effectively evaluating is for alternating current-direct current bulk power grid from now on
Preconsolidation stress and stable operation are significant
At present, the index being used for weighing the effect of influencing each other between each direct current in many straight-flow systems mainly has between DC line
Equivalent coupled impedance, node voltage interaction coefficient, many feed-ins interaction factor (MIIF) three kinds, the first index root
Network structure and parameter according to known system carry out off-line calculation and obtain；The second index is derived from node based on tide model
Relative variation relation between voltage；The third index then carries out disturbance experiments based on running mode, or the change of current is female
Line switching reactance on the spot or emulation experiment arrange node voltage and fall, it is thus achieved that the interaction factor between each straight-flow system.
Above-mentioned three kinds of methods, the system voltage reciprocation evaluation index obtained under certain conditions has uniformity, but same
Time there is also a lot of difference: first method is strong to system modeling data dependence, for huge real system, enters
Row topological analysis task amount is huge, is used for the entry evaluation of the stability of a system in planning, and application is the strongest.Additionally, the party
Method mainly considers the electrical distance between system and connecting relation, the control mode in shortcoming consideration system and the shadow of regulation equipment
Ring；Second method is based on real system and the method for operation, and the evaluation index that disturbance experiments is tried to achieve contains complexity in system
Electrical relation, closing to reality, but perturbation process needs prudent, and may be to the properly functioning generation interference of system.The third
Method, the shortcoming overcoming second method, but this method needs first to obtain grid structure and the operation of this period system
Data, resettle alternating current-direct current power flow algorithm, and the method is stronger to the structure dependency degree of electrical network.Meanwhile, above-mentioned three kinds of sides
Method is all difficult to system and influences each other the real-time assessment of degree and monitoring, it is therefore desirable to a kind of to system model dependency degree relatively
Little, analysis process is relatively simple and can be implemented in line purpose of appraisals voltage and influences each other factor on-line identification method.
Summary of the invention
The purpose of the present invention is to propose to a kind of voltage interaction factor on-line identification method of electrically-based system noise like, with
While assessing the effect of influencing each other mutual between many DC lines change of current bus, existing method complex operation is overcome to be difficult to reality
The problem of existing on-line real time monitoring.
The node voltage based on noise like that the present invention proposes influences each other the on-line identification method of the factor, comprises the following steps:
(1) using the DC converter bus of power system as test node, with the connection resistance value mark one with this test node
Value bus between 0 to 0.1, as node to be identified, utilizes following methods, respectively obtains test node and joint to be identified
The voltage noise-like signal of point:
(1～1) utilizes the phase measuring system of DC converter station in power system, tests respectively in Real-time Collection power system
Node and the voltage of node to be identified, set the width rectangularly-sampled window as Δ t, from 0 moment of sampling to Δ t,
After completing the sampling of the first period, the burst of Δ t a length of to on-line sampling carries out sensitivity identification, when sampling Δ t
It was carved into for 3 Δ t/2 moment, after completing the sampling of the second period, the burst of Δ t/2 a length of to on-line sampling and the first sampling
The burst of the rear Δ t/2 length of period forms new burst, carries out sensitivity identification, repeats said process, obtains
The voltage signal sequence of power system test node and node to be identified.
(1～2) use trend method of going, and remove the fundamental component in the voltage signal sequence of above-mentioned steps (1～1), point
Do not obtain the noise-like signal of the voltage of test node and node to be identified；
(2) calculate the noise-like signal of the node to be identified that above-mentioned (1～2) obtain and test node noise-like signal it
Between coefficient correlation, according to this coefficient correlation, the degree of correlation of node to be identified with test node is judged, if phase relation
Numerical value is between 0.00 to ± 0.30, then discriminating test node and node to be identified are that microfacies is closed, if correlation coefficient value is ± 0.30
To between ± 0.50, then discriminating test node and node to be identified are that reality closes, if correlation coefficient value ± 0.50 to ± 0.80 it
Between, then it is significant correlation between discriminating test node and node to be identified, if Calculation of correlation factor is between ± 0.80 to ± 1.00,
Then discriminating test node is highly correlated with node to be identified；
(3) method using multiple linear regression is relevant to node to be identified according to measuring node in above-mentioned steps (2)
Degree, sets up the influence each other on-line identification model of the factor of a node voltage as follows:
ΔUm=β1ΔU1+β2ΔU2+L+βiΔUi+L+βNΔUN
Wherein, i is node ID to be identified, i=1,2,3LN, Δ UmFor measuring the voltage noise-like signal of node, Δ U1、
ΔU2、ΔUiWith Δ UNIt is respectively each node voltage noise-like signal to be identified in power system, βiFor i-th joint to be identified
Point and the voltage interaction factor measured between node, βiObtaining value method be: the phase obtained according to above-mentioned steps (2)
Guan Du, if i-th node to be identified is that microfacies is closed or reality closes, then β with measuring nodeiIt is 0, if i-th node to be identified
Be significant correlation or high relevant to measuring node, then the method using successive Regression, it is calculated βi；
(4) method using detection automatically, the node to be identified that step (3) is obtained and the voltage phase measured between node
The interaction factor carries out reliability detection, and detection method is as follows:
First the factor that influenced each other by reliable voltage is designated as QM, at Δ tn-1Moment is to Δ tnIn the moment, repeat step (1)～step
Suddenly (3), obtain voltage to influence each other factor QN, at Δ tnMoment is to Δ tn+1In the moment, repeat step (1)～step (3),
Obtain voltage to influence each other factor QN+1, by QNWith QN+1Judge, if | QN-QN+1| < 10% × QNSet up, then sentence
It is scheduled on Δ tnMoment is to Δ tn+1The voltage in moment influences each other factor QN+1For unreliable, and make the Q in this periodNAs can
Influence each other factor Q by voltageM；If | QN+1-QN| >=10% × QN, then judge at Δ tnTo Δ tn+1Voltage in period is mutual
Factor of influence QN+1For reliably, and make the Q in this periodN+1Influence each other factor Q for reliable voltageM；
(5) at Δ tn+1Moment is to Δ tn+2In the moment, repeat step (1)～step (3), obtain voltage and influence each other the factor
QN+2, by QN+2Q with a upper periodMJudge, if | QN+2-QM| < 10% × QM, or
|QN+2-QM| >=10% × QM, and | QN+1-QN| >=10% × QN, then the Q of this time period is judgedN+2Mutual for reliable voltage
Factor of influence QMIf, | QN+2-QM| >=10% × QM, and | QN+1-QN| < 10% × QN, then the Q of this time period is judgedN+2
For unreliable, make the Q of this time periodN+2Equal to above-mentioned QN+1, and by QN+1As Δ tn+1To Δ tn+2The reliable voltage of period
Influence each other factor QM；
(6) with the Q obtained in step (4), step (5)MNode voltage respectively as in the first stage three periods
The on-line identification result of the factor that influences each other；
(7) repeating step (6), the node voltage obtaining each identification stage successively influences each other the on-line identification result of the factor,
Form node voltage to influence each other factor curve.
The node voltage based on noise like that the present invention proposes influences each other the on-line identification method of the factor, and its advantage is:
The inventive method can be according to the noise-like signal natively existed in power system, it is not necessary to interference test, it is possible to
Conveniently identification obtains the factor that influences each other between power system many DC converters bus.The inventive method may be used for
Interaction strength between monitoring system, provides criterion for system local stability degree, is effectively improved power system stability risk
Forecasting efficiency, reduces the cost of site test.
Accompanying drawing explanation
Fig. 1 is the linear stepwise regression method flow chart related in the inventive method.
Fig. 2 is that the node voltage related in the inventive method influences each other factor reliability overhaul flow chart.
Fig. 3 is that the node voltage that the inventive method obtains influences each other factor on-line identification result schematic diagram.
Detailed description of the invention
The node voltage based on noise like that the present invention proposes influences each other the on-line identification method of the factor, comprises the following steps:
(1) using the DC converter bus of power system as test node, with the connection resistance value mark one with this test node
Value bus between 0.1 to 0.5, as node to be identified, utilizes following methods, respectively obtains test node and to be identified
The voltage noise-like signal of node:
(1～1) utilizes the phase measuring system of DC converter station in power system, tests respectively in Real-time Collection power system
Node and the voltage of node to be identified, select sample window mobile online and realtime recurrent algorithm realize block sampling and supervises in real time
Survey, set the width rectangularly-sampled window as Δ t, from 0 moment of sampling to Δ t, complete the sampling of the first period
After, the burst of Δ t a length of to on-line sampling carries out sensitivity identification, from sampling Δ t to 3 Δ t/2 moment, completes
After the sampling of the second period, the burst of Δ t/2 a length of to on-line sampling and the rear Δ t/2 length of the first sampling periods
The burst new burst of composition, carries out sensitivity identification, repeats said process, obtain power system test node and
The voltage signal sequence of node to be identified；The factor on-line identification time interval that influences each other the node voltage making power system shortens
For Δ t/2, identification speed is accelerated；
(1～2) use trend method of going, and remove the fundamental component in the voltage signal sequence of above-mentioned steps (1～1), point
Do not obtain the noise-like signal of the voltage of test node and node to be identified；Practical power systems exists bigger inertia, electrical network
High-frequency oscillation signal is less, and therefore noise-like signal fundamental component concentrates on low-frequency range.Meanwhile, according to Chinese scholars research
As a result, Electrical Power System Dynamic information spinner to be presented by low frequency signal, little with high fdrequency component relation.Accordingly, it would be desirable to collection
To noise-like signal carry out the pretreatment such as trend, filtering and amplitude limit, to ensure to gather the validity of signal.
(2) the node voltage factor pair that influences each other is as the interaction that is primarily directed between DC converter bus, is distinguishing
Also can relate to the most neighbouring ac bus during knowledge, in real system, the possible surroundings nodes of DC converter bus is numerous,
All participate in sensitivity identification amount of calculation as the node that this node is affected relatively big, affect the speed of on-line identification, it is necessary to right
This node and surroundings nodes carry out Controlling UEP, filter out the node stronger to its influence, participate in voltage and interact
The identification process of the factor.Calculate the noise-like signal of the node to be identified that above-mentioned (1～2) obtain and the noise like of test node
Coefficient correlation between signal, according to this coefficient correlation, judges the degree of correlation of node to be identified with test node, if
Correlation coefficient value is between 0.00 to ± 0.30, then discriminating test node and node to be identified are that microfacies is closed, if correlation coefficient value
Between ± 0.30 to ± 0.50, then discriminating test node and node to be identified are that reality closes, if correlation coefficient value ± 0.50 to
Between ± 0.80, be then significant correlation between discriminating test node and node to be identified, if Calculation of correlation factor ± 0.80 to
Between ± 1.00, then discriminating test node is highly correlated with node to be identified；
(3) method using multiple linear regression is relevant to node to be identified according to measuring node in above-mentioned steps (2)
Degree, sets up the influence each other on-line identification model of the factor of a node voltage as follows:
ΔUm=β1ΔU1+β2ΔU2+L+βiΔUi+L+βNΔUN
Wherein, i is node ID to be identified, i=1,2,3LN, Δ UmFor measuring the voltage noise-like signal of node, Δ U1、
ΔU2、ΔUiWith Δ UNIt is respectively each node voltage noise-like signal to be identified in power system, βiFor i-th joint to be identified
Point and the voltage interaction factor measured between node, represent and measure node voltage noise-like signal relative to node to be identified
The sensitivity level of i voltage noise-like signal.βiObtaining value method be: the degree of correlation obtained according to above-mentioned steps (2), if
I node to be identified is that microfacies is closed or reality closes, then β with measuring nodeiIt is 0, if i-th node to be identified and measurement node
For significant correlation or high relevant, the then method using successive Regression, it is calculated βi, calculate process as shown in Figure 1；
(4) do not undergo mutation or under transient fault premise in power system grid structure, it is assumed that at each voltage signal sampling
Cycle and voltage influence each other factor Calculation of correlation factor period in, in power system, each node voltage factor of influence is constant.
The method using detection automatically, the node to be identified obtaining step (3) and the voltage measured between node interact
The factor carries out reliability detection, and detection method is as in figure 2 it is shown, be described in detail below:
The factor relatedness computation if the voltage noise-like signal of each test node and node to be identified and each voltage influence each other
Cycle in node to be identified and the voltage interaction factor measured between node constant, utilize the calculating of step (3)
Method, the factor that first influenced each other by reliable voltage is designated as QM, at Δ tn-1Moment is to Δ tnMoment, repeat step (1)～
Step (3), obtains voltage and influences each other factor QN, at Δ tnMoment is to Δ tn+1In the moment, repeat step (1)～step (3),
Obtain voltage to influence each other factor QN+1, by QNWith QN+1Judge, if | QN-QN+1| < 10% × QNSet up, then sentence
It is scheduled on Δ tnMoment is to Δ tn+1The voltage in moment influences each other factor QN+1For unreliable, and make the Q in this periodNAs can
Influence each other factor Q by voltageM；If | QN+1-QN| >=10% × QN, then judge at Δ tnTo Δ tn+1Voltage in period is mutual
Factor of influence QN+1For reliably, and make the Q in this periodN+1Influence each other factor Q for reliable voltageM；
(5) at Δ tn+1Moment is to Δ tn+2In the moment, repeat step (1)～step (3), obtain voltage and influence each other the factor
QN+2, by QN+2Q with a upper periodMJudge, if | QN+2-QM| < 10% × QM, or
|QN+2-QM| >=10% × QM, and | QN+1-QN| >=10% × QN, then the Q of this time period is judgedN+2Mutual for reliable voltage
Factor of influence QMIf, | QN+2-QM| >=10% × QM, and | QN+1-QN| < 10% × QN, then the Q of this time period is judgedN+2
For unreliable, make the Q of this time periodN+2Equal to above-mentioned QN+1, and by QN+1As Δ tn+1To Δ tn+2The reliable voltage of period
Influence each other factor QM；
(6) with the Q obtained in step (4), step (5)MNode voltage respectively as in the first stage three periods
The on-line identification result of the factor that influences each other；
(7) repeat step (6), respectively distinguished that the node voltage of period influences each other the on-line identification result of the factor,
Form node voltage to influence each other factor curve, as shown in Figure 3, it is simple to the phase interaction between on-line real time monitoring node voltage
By relation.
In practical power systems, owing to the situation moment such as switching capacitance, load fluctuation exists, therefore power system measuring knot
Miscellaneous semaphore is included in Guo, the steady-state quantity of these semaphores existing reflection system stable operation state, also there is class
Noise-like undulate quantity, referred to as noise-like signal.Noise-like signal comprises the multidate information of a lot of system, can be used to reflect
Some characteristic of system.The inventive method utilizes system node voltage noise-like signal can reflect between each bus of system exactly
The voltage noise-like signal collected, relative to this characteristic of variation relation, is processed by voltage, retains wherein effectively frequency range
Information, prepares data for following identification process.
The node voltage that the inventive method relates to influences each other the factor, and sign is the state of stable state or steady-state system temporarily.According to
System dynamic sensitivity discrimination method, copies the definition of the mutual factor of many feed-ins, characterizes node by the relation between node voltage
Between interaction relationship, choose the magnitude of voltage of studied node as state variable, choose the voltage of this near nodal bus
Being worth the actuation variable as this quantity of state, in localized network, the voltage influence approximation of research node is used linear by remaining node voltage
Relationship description.In system operation, appoint and take a period of time Δ t, due to system voltage fuctuation within a narrow range near equalization point,
Power system operation mode can be approximately considered constant, therefore voltage influence each other the factor observation data set in keep not
Become.Set up node voltage to be identified and around measure the relational model between node voltage, such as following formula:
In above formula, i represents i-th node, (comprises node to be identified at the localized network that i-th node is node to be identified
And measure node about) in include k measure node, Δ UiRepresent that the voltage class collected at node to be identified is made an uproar
Acoustical signal, Δ UjRepresent that each measures the voltage noise-like signal that node collects at remaining,Represent and measure joint
The impact that the voltage of node i to be identified is produced by the voltage change of some j, is defined herein as the node j node voltage to node i
Influence each other the factor, εiRepresent and use above-mentioned linear relationship to describe the error term brought.
Relational model between node voltage to be identified based on foundation and around measurement node voltage, appoints power taking Force system a certain
Under the method for operation, the voltage noise like data that Δ collects in the t period online carry out multiple linear regression analysis, return system
The voltages that number is between research node and interdependent node influence each other the factor.
In order to more be accurately obtained system node to be identified relative to the factor that influences each other around measuring node, the present invention selects
Select the method for linear successive Regression to carry out model coefficient and solve.
Accompanying drawing 1 is linear stepwise regression method flow chart, first with node voltage noise-like signal to be identified and measurement node electricity
The size of pressure noise-like signal partial correlation coefficient, to measuring node sequencing, introduces successively and measures node every to introduce in equation
The partial correlation coefficient of individual measurement node carries out significance test, stays and significantly measures node revocation inapparent measurement node.
Measure after node through being selected into measurement node and rejecting several times, until inclined between all measurement nodes and node to be identified
Coefficient correlation meets requirement, then till there is no to be selected in measurement node or rejecting and measure node.Linear method of gradual regression is owing to picking
Except the inessential measurement node influence to node to be identified, therefore can reduce the exponent number of regression equation, significantly improve
Computational efficiency；Insignificant measurement node during the method have ignored regression equation simultaneously, it is to avoid in regression equation, coefficient occurs
Less measure node and cause regression equation calculation time morbid state occurs.By obtaining in updating next sampling periods Δ t
Node voltage noise-like signal data, the method using linear successive Regression, the node in each Δ t period can be obtained
The voltage mutual shadow factor.
Claims (1)
1. a node voltage based on noise like influences each other the on-line identification method of the factor, it is characterised in that the method comprises the following steps:
(1) using the DC converter bus of power system as test node, using this test node connect resistance value perunit value bus between 0 to 0.1 as node to be identified, utilize following methods, respectively obtain the voltage noise-like signal of test node and node to be identified:
(1～1) utilizes the phase measuring system of DC converter station in power system, test node and the voltage of node to be identified in Real-time Collection power system respectively, set the width rectangularly-sampled window as Δ t, from 0 moment of sampling to Δ t, after completing the sampling of the first period, the burst of Δ t a length of to on-line sampling carries out sensitivity identification, from sampling Δ t to 3 Δ t/2 moment, after completing the sampling of the second period, the burst of the burst of Δ t/2 a length of to on-line sampling and the rear Δ t/2 length of the first sampling periods forms new burst, carry out sensitivity identification, repeat said process, obtain the voltage signal sequence of power system test node and node to be identified；
(1～2) use trend method of going, and remove the fundamental component in the voltage signal sequence of above-mentioned steps (1～1), respectively obtain the noise-like signal of the voltage of test node and node to be identified；
null(2) coefficient correlation between noise-like signal and the noise-like signal of test node of the node to be identified that above-mentioned (1～2) obtain is calculated，According to this coefficient correlation，The degree of correlation of node to be identified with test node is judged，If correlation coefficient value is between ± 0.30，Then discriminating test node and node to be identified are that microfacies is closed，If correlation coefficient value is between-0.50 to-0.30 and+0.30 to+0.50，Then discriminating test node and node to be identified are that reality closes，If correlation coefficient value is between-0.80 to-0.50 and+0.50 to+0.80，It it is then significant correlation between discriminating test node and node to be identified，If Calculation of correlation factor is between-1.00 to-0.80 and+0.80 to+1.00，Then discriminating test node is highly correlated with node to be identified；
(3) method using multiple linear regression, according to measuring the degree of correlation of node and node to be identified in above-mentioned steps (2), sets up the influence each other on-line identification model of the factor of a node voltage as follows:
ΔUm=β1ΔU1+β2ΔU2+…+βiΔUi+…+βNΔUN
Wherein, i is node ID to be identified, i=1,2,3 ... N, Δ UmFor measuring the voltage noise-like signal of node, Δ U1、ΔU2、ΔUiWith Δ UNIt is respectively each node voltage noise-like signal to be identified in power system, βiInfluence each other the factor for i-th node to be identified and the voltage measured between node, βiObtaining value method be: the degree of correlation obtained according to above-mentioned steps (2), if i-th node to be identified with measure node be microfacies close or reality close, then βiIt is 0, if i-th node to be identified is significant correlation or high relevant to measuring node, then the method using successive Regression, it is calculated βi；
(4) method using automatically detection, the node to be identified obtaining step (3) and the voltage measured between the node factor that influences each other carries out reliability detection, and detection method is as follows:
First influence each other factor-beta by any one voltageiReliable value be designated as QM, at Δ tn-1Moment is to Δ tnIn the moment, repeat step (1)～step (3), remember in this period that voltage influences each other factor-betaiCalculated value be Qk, at next period Δ tnMoment is to Δ tn+1In the moment, repeat step (1)～step (3), remember in this period that voltage influences each other factor-betaiCalculated value be Qk+1, by QkWith Qk+1Judge, if | Qk-Qk+1| ＜ 10% × QkSet up, then judge at Δ tnMoment is to Δ tn+1The voltage in moment influences each other factor Qk+1For unreliable, and make the Q in this periodkInfluence each other factor Q as reliable voltageM；If | Qk+1-Qk| >=10% × Qk, then judge at Δ tnTo Δ tn+1Voltage in period influences each other factor Qk+1For reliably, and make the Q in this periodk+1Influence each other factor Q for reliable voltageM；
(5) at Δ tn+1Moment is to Δ tn+2In the moment, repeat step (1)～step (3), remember in this period that voltage influences each other factor-betaiCalculated value be Qk+2, by Qk+2Q with a upper periodMJudge, if | Qk+2-QM| ＜ 10% × QM, or | Qk+2-QM| >=10% × QM, and | Qk+1-Qk| >=10% × Qk, then the Q of this time period is judgedk+2Influence each other factor Q for reliable voltageMIf, | Qk+2-QM| >=10% × QM, and | Qk+1-Qk| ＜ 10% × Qk, then the Q of this time period is judgedk+2For unreliable, make the Q of this time periodk+2Equal to above-mentioned Qk+1, and by Qk+1As Δ tn+1To Δ tn+2The reliable voltage of period influences each other factor QM；
(6) with the Q obtained in step (4), step (5)MThe on-line identification result of the factor that influences each other respectively as the node voltage of in the first stage three periods；
(7) repeating step (6), the node voltage obtaining each identification stage successively influences each other the on-line identification result of the factor, forms node voltage and influences each other factor curve.
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| CN106202932A (en) * | 2016-07-12 | 2016-12-07 | 中国石油化工股份有限公司 | A kind of method evaluating stray electrical current interference curve and interference source curve similarity |
| CN108802535B (en) * | 2018-06-27 | 2020-06-26 | 全球能源互联网研究院有限公司 | Screening method, main interference source identification method and device, server and storage medium |
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